Uncovering the genetic architecture of ME/CFS: a precision approach reveals impact of rare monogenic variation, 2025, Birch, Younger et al

[Wyva]

Camille L. Birch, Brandon M. Wilk, Manavalan Gajapathy, Shaurita D. Hutchins, Gurpreet Kaur, Donna M. Brown, Tarun K. K. Mamidi, Kathleen S. Hodgin, Alp Turgut, Jarred W. Younger & Elizabeth A. Worthey

Abstract​

Background​

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disabling and heterogeneous disorder lacking validated biomarkers or targeted therapies. Clinical variability and elusive pathophysiology hinder progress toward effective diagnostics and treatment. Core symptoms include persistent fatigue, post-exertional malaise, unrefreshing sleep, cognitive dysfunction, and pain. We tested whether an individualized, “n-of-1” genomic and transcriptomic framework combined with comprehensive, participant-informed phenotyping could reveal molecular signatures unique to each patient.

Methods​

Clinical-grade whole-genome sequencing was conducted in 31 affected individuals from 25 families, with RNA-seq performed on a subset (16 affected, 7 unaffected) using blood samples. Machine-learning assisted variant triage, transcript-aware damage prediction, and expert review identified pathogenic or likely pathogenic variants in 8 of 25 probands (32%) and 12 of 31 affected individuals (39%).

Results​

Findings revealed marked genetic heterogeneity, including large-effect rare and more common variants. Implicated pathways included ATP generation, oxidative phosphorylation, fatty acid oxidation; regulation of glycolysis, amino acid and lipid turnover; ion and solute homeostasis; synaptic signaling, excitability, oxygen transport, and muscle integrity, resilience, and post-exertional recovery; previously implicated processes. Plausible modifiers influencing disease onset, severity, and relapsing–remitting patterns and possibly explaining intrafamilial variability and inconsistent findings across studies, were also identified. Despite gene-level diversity, downstream effects converged on impaired energy production, reduced stress resilience, and vulnerability to post-exertional metabolic failure; disruptions consistent with core ME/CFS symptoms of exertional intolerance, cognitive fog, and fatigue.

Conclusions​

Our findings support the hypothesis that at least a subset of ME/CFS cases represent distinct molecular disorders that converge on shared physiological pathways. Validation in larger, more diverse cohorts will be essential to test this hypothesis and establish generalizability, but increase size alone is unlikely to resolve causation in a disorder defined by rarity, heterogeneity, and molecular complexity. We suggest that progress will require experimental designs that integrate individual-level genomic data with deep, participant-informed deep phenotyping, capturing the combined effects of rare and common variants and environmental modifiers on disease expression and progression. We believe that an individualized precision medicine framework will uncover molecular drivers and modifiers of ME/CFS previously obscured by heterogeneity, enabling biologically informed stratification, improved trial design, biomarker discovery, and targeted interventions in this historically neglected condition.

Open access (full text downloadable in PDF): https://link.springer.com/article/10.1186/s12967-025-07586-w

 

[Utsikt]

Inclusion criteria required a confirmed diagnosis of ME/CFS meeting the Fukuda 1994 definition[2], with additional cutoffs for moderate fatigue severity and frequency proposed by Jason and colleagues (2014) to reduce misclassification[15]. Primary symptoms must have been present for at least 6 months.

Fatigue severity and frequency were assessed using the DePaul Symptom Questionnaire, a standardized and widely used self-report instrument specifically developed for ME/CFS characterization[16]. While it enables structured evaluation of symptom presence, frequency, and severity, its reliance on retrospective recall may introduce variability or recall bias.

Disease severity was further quantified using a single self-report item from the Brief Fatigue Inventory[18], which measures fatigue on a 0–10 scale (0 = no fatigue; 10 = fatigue as bad as imaginable); all participants reported at least moderate fatigue of severity ≥4.

I think there is a real possibility that they might have picked out some misdiagnosed patients.

All affected individuals met Carruthers and CDC diagnostic criteria for ME/CFS.

I’m not sure if Carruthers refers to CCC or ICC, but neither are the Fukuda criteria that they mentioned earlier. Edit: CDC = Fukuda

 

[Wyva]

I’m not sure if Carruthers refers to CCC or ICC, but neither are the Fukuda criteria that they mentioned earlier.

Carruthers is the CCC.

 

[V.R.T.]

This study just shows how badly we need a much bigger whole genome sample like SequenceME

 

[neophyte32]

On Twitter, many of us have placed our trust in Amatica and its RNA sequencing. I know it's not popular here, but we have 120 patients with LC and MECFS and 60 controls. It's a start. In one month we will have the data.
In any case, the results of this study are frightening... this heterogeneity is truly problematic.

 

[Utsikt]

Carruthers is the CCC.

ICC is also Carruther’s:

https://onlinelibrary.wiley.com/doi/10.1111/j.1365-2796.2011.02428.x

 

[Utsikt]

In any case, the results of this study are frightening... this heterogeneity is truly problematic.

Do we know that these genes are pathogenic for ME/CFS though? I’m sure you’d find lots of variability in any group of patients.

 

[Jonathan Edwards]

In any case, the results of this study are frightening... this heterogeneity is truly problematic.

I am not sure why 'genetic heterogeneity' is problematic. We assume that we are dealing with differences in genes and that these are likely to mostly have small contributions to disease causation.
I am unclear how you can draw any conclusions from rare gene variants in a small population. They may well be irrelevant.

I have not read the whole paper but the abstract tells us nothing useful and seems confused.

 

[forestglip]

ICC is also Carruther’s:

https://onlinelibrary.wiley.com/doi/10.1111/j.1365-2796.2011.02428.x

Yeah, it's confusing. In other places, they refer to Carruthers. One refers to CCC, one cites ICC:

Diagnostic criteria such as the Fukuda, Canadian Consensus (Carruthers), and International Consensus Criteria define the condition
based on hallmark features.

we converted the Carruthers et al. ME/CFS diagnostic criteria[2] into HPO terms

[2] is ICC.

 

[Jonathan Edwards]

I don't know the field well enough to give an informed opinion by my impression is that the study has picked up rare variant in genes associated with a random mix of genetically determined conditions, which you would expect in any cohort. The cohort seems to have been recruited online, which is problematic because such cases are likely to be atypical. The use of Fukuda seems unnecessarily imprecise.

It would be useful to have a view from Chris Ponting on this. But I think there are regular members here who may be able to shed light.

I may be wrong but I didn't see any control group?

 

[Utsikt]

may be wrong but I didn't see any control group?

No idea what this actually means, maybe the figure will tell us more when it’s published:

Participants
We enrolled 25 probands (38 individuals; spanning 31 affected participants and 7 healthy first-degree relatives). This included five affected-unaffected duos, three all-affected duos/trios, two trios with mixed unaffected/ affected individuals, and 15 singletons.

All affected individuals met Carruthers and CDC diagnostic criteria for ME/CFS.

All probands and all but one affected individual were female; this male participant was included as an affected son in a mother–son duo.

The mean age was 46.8 years (41.5 for affected participants, 71.7 for unaffected relatives).

Race and ethnicity self-reported at enrollment agreed with that estimated from WGS data, showing a predominantly European cohort, with six individuals of substantial African ancestry and three with significant American admixture (Supplemental Figure 2).

Disease onset ranged; eight in childhood, six in adolescence, nine in their twenties, and eight in their thirties. Sixteen reported gradual onset (four with identified exacerbating events), while 14 reported sudden onset: five with identified precipitating infections, six with non-infectious events, and three without any identified event.

One participant did not complete the questionnaire but provided information via phone and in-person screening.

All unaffected first-degree relatives were confirmed asymptomatic by interview and questionnaire.

DNA and RNA were extracted and sequenced for all; due to sample storage issues at HudsonAlpha, samples were lost and RNA-seq was completed for 16 affected and 7 unaffected participants.

 

[jnmaciuch]

The premise of the paper is basically asking: “Could a group of genetics researchers pull something out of the grab-bag of potentially pathogenic variants that every living human walks around with and come up with an educated guess for why participants X Y and Z might have [insert clinical symptom] and participants A B and C do not.”

Unsurprisingly, the answer is yes they can. Beyond this basic question, there are several parts of the analysis where I’m just not sure what the reasoning was.

If you wanted to do this systematically, you would likely need thousands of participants with extremely detailed symptom information. And it still wouldn’t give you much information about the etiology of ME/CFS at all—it might just enable us to predict something like “under the physiological strain of the ME/CFS disease state, what genetic factors make some pwME more likely to end up with OI or rapid muscle weakness as one of their primary symptoms?”